A multi-echelon reverse logistics network design for product recovery—a case of truck tire remanufacturing

Abstract

Due to increasing environmental deterioration, government regulations, social responsibilities, resource reduction, and economic factors, many companies are engaged in the product recovery business. Product recovery refers to the set of activities designed to reclaim value from a product at the end of its useful life. Due to the increasing number of vehicles in the country like India, large quantities of used tires are generated every year, and proper disposal of these used tires creates a significant problem in the day-to-day life. An alternative way to recover the value (tire remanufacturing also called retreading) from the used tire is proposed in this work. The implementation of such remanufacturing system usually requires an appropriate reverse logistics network for choosing the physical locations, facilities, and transportation links to convey the used products from customers to the remanufacturing facility and from there to secondary markets. The main objective of this work is to develop a mixed integer nonlinear programming model for maximizing the profit of a multi-echelon reverse logistics network and also to present a real-life case study of truck tire remanufacturing for the secondary market segment. The proposed model is solved using LINGO 8.0 optimization solver which provides the decisions related to the number of facilities to open, their locations, and also the allocation of the corresponding product flows. Finally, it is concluded that the choice of using retreaded tires is a profitable one by the way of cost reduction. Sensitivity analysis of the model is also presented to find the maximum allowable distance between the customers and initial collection points.